Evaluation of Field Germination of Soybean Breeding Crops Using Multispectral Data from UAV
The use of multispectral aerial photography data contributes to the study of soybean plants by obtaining objective data. The evaluation of field germination of soybean crops was carried out using multispectral data (MSD). The purpose of this study was to develop ranges of field germination of soybea...
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Published in | Agronomy (Basel) Vol. 13; no. 5; p. 1348 |
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Abstract | The use of multispectral aerial photography data contributes to the study of soybean plants by obtaining objective data. The evaluation of field germination of soybean crops was carried out using multispectral data (MSD). The purpose of this study was to develop ranges of field germination of soybean plants according to multispectral survey data from an unmanned aerial vehicle (UAV) for three years (2020, 2021, and 2022). As part of the ground-based research, the number of plants that sprang up per unit area was calculated and expressed as a percentage of the seeds sown. A DJI Matrice 200 Series v2 unmanned aerial vehicle and a MicaSense Altum multispectral camera were used for multispectral aerial photography. The correlation between ground-based and multispectral data was 0.70–0.75. The ranges of field germination of soybean breeding crops, as well as the vegetation indices (VIs) normalized difference vegetation index (NDVI), normalized difference red edge index (NDRE), and chlorophyll index green (ClGreen) were calculated according to Sturges’ rule. The accuracy of the obtained ranges was estimated using the mean absolute percentage error (MAPE). The MAPE values did not exceed 10% for the ranges of the NDVI and ClGreen vegetation indices, and were no more than 18% for the NDRE index. The final values of the MAPE for the three years did not exceed 10%. The developed software for the automatic evaluation of the germination of soybean crops contributed to the assessment of the germination level of soybean breeding crops using multispectral aerial photography data. The software considers data of the three vegetation indices and calculated ranges, and creates an overview layer to visualize the germination level of the breeding plots. The developed method contributes to the determination of field germination for numerous breeding plots and speeds up the process of breeding new varieties. |
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AbstractList | The use of multispectral aerial photography data contributes to the study of soybean plants by obtaining objective data. The evaluation of field germination of soybean crops was carried out using multispectral data (MSD). The purpose of this study was to develop ranges of field germination of soybean plants according to multispectral survey data from an unmanned aerial vehicle (UAV) for three years (2020, 2021, and 2022). As part of the ground-based research, the number of plants that sprang up per unit area was calculated and expressed as a percentage of the seeds sown. A DJI Matrice 200 Series v2 unmanned aerial vehicle and a MicaSense Altum multispectral camera were used for multispectral aerial photography. The correlation between ground-based and multispectral data was 0.70–0.75. The ranges of field germination of soybean breeding crops, as well as the vegetation indices (VIs) normalized difference vegetation index (NDVI), normalized difference red edge index (NDRE), and chlorophyll index green (ClGreen) were calculated according to Sturges’ rule. The accuracy of the obtained ranges was estimated using the mean absolute percentage error (MAPE). The MAPE values did not exceed 10% for the ranges of the NDVI and ClGreen vegetation indices, and were no more than 18% for the NDRE index. The final values of the MAPE for the three years did not exceed 10%. The developed software for the automatic evaluation of the germination of soybean crops contributed to the assessment of the germination level of soybean breeding crops using multispectral aerial photography data. The software considers data of the three vegetation indices and calculated ranges, and creates an overview layer to visualize the germination level of the breeding plots. The developed method contributes to the determination of field germination for numerous breeding plots and speeds up the process of breeding new varieties. |
Audience | Academic |
Author | Rasulova, Victoria Zakharova, Natalia Rebouh, Nazih Y Kucher, Dmitry E Litvinov, Maxim Gureeva, Elena Golovina, Ekaterina Polukhin, Andrey Lobachevsky, Yakov Ali, Abdelraouf M Yatchuk, Pavel Kurbanov, Rashid Panarina, Veronika |
Author_xml | – sequence: 1 givenname: Rashid orcidid: 0000-0003-0139-6433 surname: Kurbanov fullname: Kurbanov, Rashid – sequence: 2 givenname: Veronika surname: Panarina fullname: Panarina, Veronika – sequence: 3 givenname: Andrey surname: Polukhin fullname: Polukhin, Andrey – sequence: 4 givenname: Yakov surname: Lobachevsky fullname: Lobachevsky, Yakov – sequence: 5 givenname: Natalia orcidid: 0000-0001-9035-0247 surname: Zakharova fullname: Zakharova, Natalia – sequence: 6 givenname: Maxim surname: Litvinov fullname: Litvinov, Maxim – sequence: 7 givenname: Nazih Y. orcidid: 0000-0002-8621-6595 surname: Rebouh fullname: Rebouh, Nazih Y. – sequence: 8 givenname: Dmitry E. surname: Kucher fullname: Kucher, Dmitry E. – sequence: 9 givenname: Elena orcidid: 0000-0002-1740-7937 surname: Gureeva fullname: Gureeva, Elena – sequence: 10 givenname: Ekaterina surname: Golovina fullname: Golovina, Ekaterina – sequence: 11 givenname: Pavel surname: Yatchuk fullname: Yatchuk, Pavel – sequence: 12 givenname: Victoria surname: Rasulova fullname: Rasulova, Victoria – sequence: 13 givenname: Abdelraouf M. orcidid: 0000-0002-3564-7352 surname: Ali fullname: Ali, Abdelraouf M. |
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SubjectTerms | Aerial photography Agricultural industry breeding Calibration Cameras Chlorophyll Crops digital agriculture Drone aircraft Germination Laboratories Mathematical analysis multispectral data New varieties Normalized difference vegetative index Plant breeding Plants (botany) remote sensing Seeds Software Soybean Soybeans Surveys unmanned aerial vehicle Unmanned aerial vehicles Vegetation |
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Title | Evaluation of Field Germination of Soybean Breeding Crops Using Multispectral Data from UAV |
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